code: def one_hot(
      indices: Union[tf.Tensor, tf.Variable],
      depth: int,
      /,
      *,
      on_value: Optional[Number] = None,
      off_value: Optional[Number] = None,
      axis: Optional[int] = None,
      dtype: Optional[tf.DType] = None,
      device: Optional[str] = None,
      out: Optional[Union[tf.Tensor, tf.Variable]] = None,
  ) -> Union[tf.Tensor, tf.Variable]:
      return tf.one_hot(
          indices,
          depth,
          on_value=on_value,
          off_value=off_value,
          axis=axis,
          dtype=dtype,
      )
  
imports: import numpy
  from numbers import Number
  from typing import Union, List, Optional, Sequence, Tuple
  import tensorflow
  import ivy
  from ivy.func_wrapper import with_unsupported_dtypes
  from ivy.functional.ivy.creation import _asarray_to_native_arrays_and_back, _asarray_infer_device, _asarray_infer_dtype, _asarray_handle_nestable, NestedSequence, SupportsBufferProtocol, _asarray_inputs_to_native_shapes
  from .None import backend_version
label_desc: Use image node_id 20 for calling a global function with example usage: one_hot() and returns: tf